OPTIMIZATION AND PERFORMANCE ENHANCEMENT OF PUBLIC BUS TRANSPORTATION SYSTEMS: A CASE STUDY APPROACH

Abstract

This study introduces an optimized scheduling approach tailored to the Urban and Suburban Transport Company of Constantine (USTCC), addressing persistent discrepancies between planned and actual bus schedules. These mismatches often disrupt punctuality and diminish passenger satisfaction. The proposed method employs a data-driven analysis of timetable deviations, using Root Mean Square Error (RMSE) to quantify gaps between theoretical and real-world performance. By pinpointing synchronization inefficiencies, the model suggests precise adjustments to departure and arrival times, ensuring better alignment with operational realities. This refinement enhances service reliability and user experience without compromising feasibility. The optimization process involves three steps: (i) identifying major timing gaps by route and time slot, (ii) adjusting schedules to reduce delays, and (iii) assessing improvements using key metrics. Findings show this approach cuts average delays, boosts reliability, and aligns operations more closely with passenger needs. The method enhances efficiency while maintaining service quality, making it a practical solution for transit scheduling challenges.

The findings confirm the effectiveness of this method as a means for continuously enhancing urban transport systems. Additionally, the approach is versatile and can be modified for other networks facing comparable inefficiencies. By integrating real-time data and dynamic factors like passenger demand, service frequency, and vehicle capacity, this model offers potential for scalable, data-informed optimizations in various transit settings. Its adaptability supports sustainable improvements, making it a valuable tool for modernizing public transportation. The framework’s ability to evolve with changing conditions ensures long-term relevance, enabling smarter, more efficient mobility solutions across different urban environments.